Some researchers try to not use the "traditional" learned video compression framework. Wu et al. [1]} view video compression as an image interpolation problem and propose to interpolate target frame from references in a hierarchical manner, where the residual of the interpolation is then compressed via a RNN-based image compression network. Newest works [2]}, [3]} try to directly capture spatiotemporal relationships using a 3D auto-encoder and autoregressive prior model. These methods outperform H264, but worse than HEVC and other learned methods.
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